An implantable medical apparatus which executes cardiovascular control operations may evaluate cardiac electrical signals for many purposes. A cardiac control instrument analyzes cardiac signals to determine how well the cardiovascular system is performing. As a result of this analysis, the instrument responds to the detection of predetermined criteria by automatically initiating control operations. One class of signal analyzers examines the time sequence of cardiac signal amplitudes to detect changes in the morphology, or shape, of the cardiac waveform which are indicative of cardiac function.
Most common cardiac control devices, including cardiac pacemakers, employ a rudimentary form of signal morphology analysis. These devices sense the amplitude of intracardiac electrogram signals and compare the instantaneous sensed amplitude to a preset threshold value. If the signal amplitude is larger than the threshold, the pacemaker inhibits its pacing stimulus generation response. Noise, including cardiac signals arising from sources other than those intended for measurement, adversely influences this simple control mechanism.
More sophisticated morphology analysis techniques are required for controlling other, more complex, diagnostic and therapeutic operations. One example of a function requiring a sophisticated analysis technique is the reliable detection of cardiac arrhythmias. The difficult problem of cardiac arrhythmia detection, including detection of ventricular tachycardia and fibrillation, has been addressed using many cardiac signal morphology procedures. One effective procedure, as proven in tests involving both intracardiac signal and surface electrocardiograms and reported by D. Lin et al. in "Identification of Ventricular Tachycardia Using Intracavitary Ventricular Electrograms: Analysis of Time and Frequency Domain Patterns", PACE, Vol. 11, pages 1,592-1,606 (1988), is the correlation of the detected signal with a previously recorded signal waveform which is known to characterize a particular diagnostic condition. Correlation is the summation of the products of point-by-point multiplications of two waveform sequences for the purpose of deriving a standard of similarity between the two waveform sequences. Unfortunately, correlation analysis requires such computational complexity that it is impractical in an implanted device. Because the device expends energy on each computational step and correlation requires so many computations, the lifetime of an implanted device performing correlation would be unreasonably short or the battery size too large for practical usage.
In many cardiac arrhythmia patients, there is a critical need for a reliable method for differentiating sinus tachycardia and atrial tachyarrhythmias from ventricular tachycardia (VT). If a cardiac control device had the capability of distinguishing sinus tachycardia from VT, it could monitor heart activity to determine whether there was a need to perform a procedure for terminating heart disorders or arrhythmias. (This procedure is called cardioversion). Most early methods for differentiating sinus tachycardia from VT were based on analyzing the timing between consecutive R-waves within a sensed electrocardiogram. Diagnostic devices would determine the R-wave rate and compare it to a predetermined maximum rate of sinus tachycardia. Some devices would also analyze the rate stability of the heart and the quickness of the onset of rate changes. Because these rate change characteristics of the R-wave always accompany ventricular tachycardias, a device controlled by these procedures will consistently detect and respond to such arrhythmias. Unfortunately, a normally functioning heart also may exhibit these rate change characteristics. For example, such rate changes may indicate only that the patient is exercising. The morphology of the intracardiac electrogram usually displays morphological differences depending upon whether the heartbeat proceeds in a normal sinus rhythm (SR) sequence of electrical activation or an abnormal ventricular tachycardia (VT) sequence. Therefore, in addition to monitoring the rate, it is beneficial for a device to analyze the morphology of cardiac signals.
Langer et al., in U.S. Pat. No. 4,202,340, entitled "Method and Apparatus for Monitoring Heart Activity, Detecting Abnormalities, and Cardioverting a Malfunctioning Heart", issued May 13, 1980, describe an antitachycardia pacing system which detects arrhythmias by analyzing the morphology of cardiac signals. The arrhythmia detection system of the Langer et al. invention analyzes cardiac signal morphology statistically by developing a probability density function, which compares the amplitudes and locations of points in an analyzed cardiac waveform with the expected locations of points of a predetermined "normal" waveform. When the waveform becomes irregular, as measured by the probability density function, this indicates an abnormal cardiac function. The probability density function defines the fraction of time, on the average, that a signal spends between two amplitude limits. The basis for decision in this process is that the amount of time spent at baseline in each cardiac cycle is significantly longer during sinus rhythm than during ventricular tachycardia or ventricular fibrillation. The probability density function is the measure of time the signal spends away from the isoelectric baseline. It is markedly different during ventricular fibrillation than it is during normal sinus rhythm. The probability density function detects ventricular fibrillation (VF) reliably since the signal is seldom near the isoelectric line during VF. However, the probability density function is not nearly as reliable for distinguishing sinus tachycardia from ventricular tachycardia.
The probability density function approach to arrhythmia detection is often unreliable because a ventricular tachycardia signal often appears the same as a sinus tachycardia cardiac signal to a probability density detector. Furthermore, if the predetermined "normal" waveform is not properly synchronized with the analyzed waveform, the device may incorrectly classify a waveform as an indication of a fibrillation condition upon the occurrence of some forms of high rate, or even low rate, ventricular tachycardia, in addition to true ventricular fibrillation. A particular problem occurs in the presence of ventricular conduction abnormalities. Defibrillation, which is triggered by a high rate tachycardia, is acceptable because high rate tachycardia can be fatal if it occurs at an elevated rate so considerable that not enough blood is pumped to sustain the body. However, generating defibrillation pulses in the event of low rate, non-life threatening tachycardia is inappropriate and possibly harmful.
Correlation analysis of intra-cavitary ventricular electrograms is another technique for analyzing cardiac waveform morphology. Correlation of signals improves specificity of arrhythmia recognition. Correlation waveform analysis is a reliable technique for discriminating ventricular tachycardia from sinus rhythm. It has been used for over two decades in the analysis of surface lead morphology as well as for analyzing esophageal electrograms, intra-ventricular electrograms and intra-atrial electrograms. However, the number of computations correlation requires is too demanding for usage in the low energy environment of an implantable device.
One technique for performing standard correlation, called piecewise correlation analysis, involves multiplying the waveform sequences in a section by section manner. This provides for a reduction in the number of required computations by limiting the correlation procedure to operate only in the vicinity of the R-wave. In one example of piecewise correlation, a signal processing system defines a representative "normal" signal by measuring a ventricular electrogram signal template when the heart is functioning with a normal sinus rhythm. The system specifies this template by "windowing" the waveform with respect to time, detecting the QRS complex of the cardiac signal and storing a predetermined number of samples before and after the QRS complex. For example, a waveform window may include 64 samples, which contain the QRS complex and are acquired at a 1,000 Hz rate. The system averages a number of these waveform windows for a preset number of cardiac cycles with the QRS complex for each cardiac cycle occurring at the same sample location within the window. After sampling and storing the template waveform, the system samples the ventricular electrogram at the same rate and for the same number of samples as was done when acquiring the template samples. The device correlates these samples with the average sinus rhythm template on a beat-by-beat basis.
U.S. Pat. No. 5,000,189, entitled "Method and System for Monitoring Electrocardiographic Signals and Detecting a Pathological Cardiac Arrhythmia such as Ventricular Tachycardia", issued to R. D. Throne et al. on Mar. 19, 1991, describes another method for comparing cardiac signals for the purpose of detecting arrhythmia conditions. The Throne et al. system monitors electrocardiographic signals for the purpose of detecting cardiac arrhythmias by processing and analyzing such signals when the heart is functioning in an unknown state and comparing these processed signals to heart signals obtained when the heart was operating in a known state. This system defines a known signal template by acquiring electrocardiogram signals when the heart is operating in a known state, calculating the first derivative of the signal, determining the location of zero crossings of the first derivative signal and defining time partitions for analyzing subsequent cardiac signals at the time locations of the zero crossings. The template is determined by summing the samples in each partition. The first derivative of subsequent signals, which are acquired when the heart is functioning in an unknown state, is calculated and summed within the partitions defined by the template signal. The partition sums for the subsequent samples and the template samples are compared to determine whether the unknown signals have the same characteristic structure as the known template signals. The method and system of the Throne et al. patent improves upon the standard correlation procedure by requiring much simpler computations and demanding less power for performing calculations. It is an advantage that the Throne et al. system functions independently of fluctuations of the zero level (baseline) between ventricular electrocardiograms and changes in electocardiogram amplitudes.
The previously known morphology-based arrhythmia detection procedures operate on the presumption that the monitored signal must have the same form, in terms of timing and phase, as a template signal which was acquired when the heart was functioning in a known cardiac state. These procedures consider any changes in form to be errors, which are to be tolerated to some degree, but are errors nonetheless. Moreover, previously known morphology-based arrhythmia detection procedures respond to single large amplitude noise spikes by including an aberrant sample amplitude in a calculation for determining a physiological parameter. This single noise sample will often greatly skew the parameter value resulting from the calculation in a manner which is out of perspective to its physiological importance.
It is, therefore, a primary object of the present invention to provide for analysis of cardiac electrical signals in a manner which considers physiological variability in signal morphology to be a normal occurrence, so that normal physiological variations in the signal will not contribute to an increase in an "error" signal in the derived physiological parameter. This is done by selecting a physiologically normal cardiac electrical signal, defining an amplitude window which delineates a range of signal amplitudes bracketing the amplitude of the normal cardiac electrical signal, and comparing subsequent cardiac signals to the normal window in a sample-by-sample manner. The relative number of samples falling outside the amplitude window, rather than the cumulative amplitude of the differences between samples, is used to analyze signal morphology for the purpose of detecting cardiac arrhythmias.
Another important object of the present invention is to reduce the emphasis of single noise spikes to a reasonable physiological importance.
It is a further object of the present invention to provide a system for reliably detecting abnormal ventricular signals, based on the morphology of such signals, in which the system accepts physiological variability as a normal condition and is not overly sensitive to the occurrence of short-term noise spikes.
An additional object of the present invention is to provide a low power demand device and a reliable detection circuit to accurately identify ventricular tachycardia and ventricular fibrillation.
Further objects and advantages of this invention will become apparent as the following description proceeds.